Asia-Pacific Journal of Regional Science最新文献

As one of the most polluted cities in Latin America, Medellín faces recurrent air quality crises, driven by transportation emissions and topographical constraints that exacerbate pollution retention. At the same time, the city is recognized as a hub for urban innovation, implementing policies aimed at sustainable mobility and green infrastructure. Therefore, we examined the decoupling relationships between economic growth and carbon emissions in Medellín’s metropolitan area, Colombia’s second-largest urban center, from 2000 to 2023. Using the Logarithmic Mean Divisia Index (LMDI) and the Tapio decoupling elasticity model, this study integrated updated datasets, including Copernicus Atmosphere Monitoring Service (CAMS) emission inventories and local air quality monitoring data. Results indicated a predominance of weak decoupling with GDP growth at an annual rate of 5.66% while emissions increased marginally at 0.25%. Sectoral analysis revealed that the tertiary sector, responsible for 72% of GDP and 59% of emissions, exhibited alternating periods of weak (15) and strong decoupling (6), driven by efficiency improvements and structural changes. In contrast, the secondary sector consistently reduced contributions to production and carbon emissions after 2008 configuring 7 instances of strong decoupling in the last years. Population growth was identified as a major inhibitor of decoupling, contributing to rising emissions in the transportation sector, which remains as the primary source of urban emissions. Energy and carbon intensity reductions contributed positively to decoupling, particularly in commercial and service-based activities. These findings highlight the need for deeper targeted policy interventions and sector-specific strategies to accelerate regional decoupling and support sustainable urban development.

Changes in the effects of climate on agricultural yield are becoming common in the literature. The present study investigated how both climatic and socioeconomic variables affect means and variations in crop yield. We examined factors that affect the yields of two major crops, wheat and maize, cultivated in different seasons in Madhya Pradesh, India. For empirical analysis, we employed the Just and Pope production function, covering the period from 1999 to 2017 based on the latest district-level available data of Madhya Pradesh. An increase in rainfall enhanced the mean yield of both crops in Central India, showing the yield of these crops is highly dependent on rainfall. Average temperature and number of extreme cold days adversely affected the wheat yield in the region. Furthermore, an increase in fertilizer consumption raised mean crop yield, but it was not uniform, because this leads to an increase in variation of crop yields. The findings also confirmed the presence of an inverted ‘U’-shaped relationship between the mean maize yield and rainfall. However, there was a ‘U’ shaped relationship between mean wheat yield and temperature. Surprisingly, irrigation showed a differential impact on mean yield in different seasons. Normally, irrigation is a risk reducing input and diminishes variance in yields. These results provide policy insights to state and local governments for adaptation measures against climate change to protect the mean yield and control variations in yield of these major crops in the central part of India.

In the context of rising climate pressures, the Middle East and North Africa (MENA) Region is confronted with the challenge of reconciling its high economic growth with environmental sustainability. Despite sustained global efforts toward achieving Sustainable Development Goal 13 (climate action), most countries in the region are still hampered by resource dependency, a lack of effective policy implementation, and ongoing ecological pressures. This paper looks at how information and communication technology (ICT), human development (HD), military expenditures (ME), and renewable energy (REC) affect the environmental quality (ENQ) based on three indicators, i.e., carbon dioxide emissions (CO₂e), ecological footprint (EFP) and greenhouse gas emissions (GHGe) in ten MENA countries between 2001 and 2022 within the Environmental Kuznets Curve (EKC) framework. Employing the Pooled Mean Group (PMG) estimation model, the results show that although ME and NREC worsen the environment by increasing CO₂e, HD, ICT and REC improve ENQ by reducing CO₂e in the long run. However, HD, ICT, REC, NREC and FDI worsen the environment by increasing EFP, while ICT improves the environment by mitigation. Meanwhile, HD, ME and REC decrease GHGe, while ICT and NREC increase them. Furthermore, all three models support the EKC hypothesis in the MENA Region. Based on the overall findings, MENA nations must establish a conducive policy framework by adopting green growth strategies, promoting clean energy, leveraging ICT for sustainability, integrating eco-friendly practices into military operations, and allocating defense budgets to environmental initiatives, all of which are crucial for advancing climate action in the region.

Coffee is one of the most widely consumed beverages globally, with its consumption influenced by socio-economic factors, such as income levels, pricing, and regional preferences. This study examined the relationships between income and coffee consumption across different regions to analyze whether coffee behaves as a normal good. Using an unbalanced panel dataset from 53 countries, we incorporated key economic variables including Gross Domestic Product (GDP) per capita, coffee and tea consumption, and the prices of ground coffee and tea. A fixed-effects regression model was employed to assess the impact of income variations on coffee intake. The findings revealed significant regional disparities. For the European and African & Middle Eastern Regions, income showed a positive effect on coffee consumption when grouped with all variables. For the Asia–Pacific (APAC) and American regions, income within the regression showed no statistical significance whatsoever. Therefore, income appears, for half the regions, to be significant in determining coffee consumption, i.e., the more money one has, the more coffee they are able to consume, which reiterates that coffee is a normal good. These results contribute to the existing literature by providing a comparative regional analysis of income-driven coffee consumption. The findings also have practical implications for coffee producers, policymakers, and businesses seeking to understand market demands. Understanding regional coffee trends can support demand forecasting and pricing strategies. However, future studies should also examine consumer behavior and marketing dynamics.

This study utilized geospatial techniques and machine learning (ML) algorithms, viz. Random Forest and XGBoost, for predicting the air quality and the AirQ+ model for assessing health risks in urban environments. We analyzed the annual variations in sulfur dioxide (SO₂) and nitrogen dioxide (NO₂) levels of five Indian metropolitan cities from 2019 to 2022. Preliminary analysis indicated the highest levels of NO₂ and SO₂ in Delhi and Kolkata as compared to other metropolises. Kolkata had an 11% increase in SO₂ concentrations in 2022 compared to 2019, while Delhi had a 20% increase in NO₂ concentrations in 2022 compared to 2019. The air pollutant levels predicted by ML algorithms were analyzed in the AirQ+ model for health risks. The health impact assessment conducted using the AirQ+ model revealed concerning trends. In 2023, particulate matter (PM_2.5) was attributed to 20.26% of respiratory disease cases per 100,000 population in Delhi, followed by NO₂, accounting for 11.01%. In Kolkata, SO₂ was responsible for 3.21% of respiratory disease cases. By implementing this approach, policymakers can estimate the air pollution levels and potential respiratory disease health risks. This knowledge can help them formulate targeted interventions, such as implementing pollution control measures, managing health risks, and issuing health advisories, to protect public health and improve air quality in cities.

New Zealand has one of the highest immigration rates in the developed world, resulting in a high share of foreign-born residents. Its population is highly urbanized, spatially uneven, ethnically diverse, and includes a significant indigenous Māori population. This paper synthesizes two decades of research on migrant social capital in New Zealand, drawing on data from multiple waves of the New Zealand General Social Survey and the Adult Literacy and Life Skills Survey. These datasets provide insights into community participation, volunteering, perceptions of safety and inclusion, and electoral engagement. We draw two main conclusions from our synthesis. First, although migrants arrive with limited local social capital, they gradually build bonding, bridging, and linking, social capital over time. In addition, reported experiences of discrimination decline with longer residence. However, pooled survey data reveal variation in these patterns across time. Second, social capital investment is shaped by the spatial distribution of ethnic groups. Migrants are more likely to engage in bridging social capital in regions where their group is underrepresented, and in bonding social capital in communities where ethnic clustering occurs.

We analyzed water pollution in the Ganges River caused by tanneries in Kanpur, India. Specifically, we examined the merits of a claim made recently in the literature that unitizing or merging polluting tanneries can improve water quality in the Ganges. We modeled the (nge 2) polluting tanneries in Kanpur as a Cournot oligopoly and derived the equilibrium output of leather, profits, and social welfare. Second, we permitted (m<n) tanneries to merge and determined when the (m)-tannery unitization is profitable to the unitized entity. Third, the ((n-m)) non-unitized tanneries were better off with unitization. Finally, our findings demonstrated that (m)-tannery unitization increases the industry price of leather and lowers social welfare. In conclusion, we discuss the implications of these findings for improved water quality in the Ganges.

Amid growing concerns about global environmental sustainability, increasing attention has been directed toward the relationships between economic growth, stringent environmental policies, and energy consumption patterns. However, a critical gap remains in understanding how these factors collectively influence environmental sustainability in G-7 economies. This empirical study sought to bridge this gap by examining the heterogenous effects of economic growth, environmental policy stringency, energy intensity, foreign direct investment, renewable energy consumption, and non-renewable energy consumption on environmental sustainability. Load capacity factors were employed as an innovative metric to assess ecological demands relative to biocapacity. Utilizing a non-parametric Method of Moments Quantile Regression (MMQR) approach on panel data spanning 1993–2023, the findings revealed that environmental policy stringency, energy intensity, renewable energy consumption, and foreign direct investment have positive and significant impacts on environmental sustainability across heterogenous quantiles. Conversely, economic growth and non-renewable energy consumption exerted negative and significant influences on environmental sustainability across most quantiles. In conclusion, we recommend prioritizing policies that promote a transition from non-renewable to renewable energy sources through incentives such as tax reductions and subsidies. Additionally, increased investments in green technologies and enforcement of stringent environmental regulations, including carbon taxes on excessive greenhouse gas emissions, are needed to enhance environmental sustainability in the G-7 economies.

This article provides a comprehensive analysis of the growing regional divide in Kazakhstan, examining the dimensions and implications of spatial inequality in a country that has experienced robust economic growth in recent decades. We employ convergence analysis, a Regional Development Trap Index, and a Regional Competitiveness Index to measure territorial inequalities across Kazakhstan. Our findings reveal that whilst the country has achieved relatively rapid aggregate economic growth, this has been accompanied by a widening territorial divide. Wealth and economic activities are becoming increasingly concentrated in major urban centres, such as Almaty and Astana, whilst other regions—particularly those in the south—continue to lag significantly behind. These results highlight an increasingly polarised nation, where certain regions benefit from economic dynamism and Kazakhstan’s international integration, whilst others remain trapped in low-growth equilibria. The article concludes by offering targeted policy recommendations aimed at promoting inclusive growth, enhancing regional competitiveness, and reducing spatial disparities throughout Kazakhstan.